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首页> 外文期刊>International Journal of Geographical Information Science >The effect of temporal sampling intervals on typical human mobility indicators obtained from mobile phone location data
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The effect of temporal sampling intervals on typical human mobility indicators obtained from mobile phone location data

机译:时间采样间隔对从手机位置数据获得的典型人类移动性指标的影响

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摘要

Mobile phone location data have been extensively used to understand human mobility patterns through the employment of mobility indicators. The temporal sampling interval (TSI), which is measured by the temporal interval between consecutive records, determines how well such data can describe human activities and influence the values of human mobility indicators. However, systematic investigations of how the TSI affects human mobility indicators remain scarce, and characterizing those relationships is a fundamental research question for many related studies. This study uses a mobile phone location dataset containing 19,370 intensively sampled individual trajectories (TSI 5 minutes) to systematically assess the impacts of the TSI on four typical mobility indicators that describe human mobility patterns from different aspects, which are movement entropy, radius of gyration, eccentricity, and daily travel frequency. We find that different TSIs have complex impacts on the values of different mobility indicators. Specifically, (1) coarser TSIs tend to underestimate the values of the four selected indicators with different degrees; (2) the degrees of underestimation vary significantly among users for eccentricity and daily travel frequency but exhibit high inter-user consistency for radius of gyration and movement entropy. The above findings can help better understand the variations among human mobility studies.
机译:通过使用移动性指标,移动电话位置数据已被广泛用于理解人类的移动性模式。由连续记录之间的时间间隔测量的时间采样间隔(TSI)决定了此类数据可以很好地描述人类活动并影响人类流动性指标的值。但是,对于TSI如何影响人类流动性指标的系统研究仍然很少,而对这些关系进行表征是许多相关研究的基础研究问题。这项研究使用包含19,370个密集采样的个人轨迹(TSI <5分钟)的移动电话位置数据集来系统地评估TSI对四种典型的移动性指标的影响,这些指标从不同方面描述了人类的移动性模式,即运动熵,回转半径,偏心率和每日旅行频率。我们发现,不同的TSI对不同流动性指标的值具有复杂的影响。具体而言,(1)较粗糙的TSI倾向于低估不同程度的四个选定指标的值; (2)在偏心率和每日行进频率方面,低估程度在用户之间差异很大,但在用户间的回转半径和运动熵方面表现出较高的一致性。上述发现可以帮助更好地了解人类流动性研究之间的差异。

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    Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan, Hubei, Peoples R China|Fuzhou Univ, Spatial Informat Res Ctr Fujian Prov, Fuzhou, Fujian, Peoples R China;

    Univ Tennessee, Dept Geog, Knoxville, TN 37996 USA;

    Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen, Peoples R China;

    Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan, Hubei, Peoples R China|Wuhan Univ, Collaborat Innovat Ctr Geospatial Technol, Wuhan, Hubei, Peoples R China;

    Shaanxi Normal Univ, Sch Geog & Tourism, Xian, Shaanxi, Peoples R China;

    Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen, Peoples R China;

    Fuzhou Univ, Spatial Informat Res Ctr Fujian Prov, Fuzhou, Fujian, Peoples R China|Fujian Collaborat Innovat Ctr Big Data Applicat G, Fuzhou, Fujian, Peoples R China;

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  • 正文语种 eng
  • 中图分类
  • 关键词

    Human mobility; temporal sampling intervals; mobile phone location data; modifiable temporal unit problem(MTUP);

    机译:人口流动性;时间采样间隔;手机位置数据;可修改的时间单位问题(MTUP);

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